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Sergio M. Vicente-Serrano, Santiago Beguería, Jorge Lorenzo-Lacruz, Jesús Julio Camarero, Juan I. López-Moreno, Cesar Azorin-Molina, Jesús Revuelto, Enrique Morán-Tejeda, and Arturo Sanchez-Lorenzo

drought indices to identify hydrological droughts in river discharges and reservoir storages in central Spain, and Zhai et al. ( Zhai et al. 2010 ) compared the relationship between the standardized precipitation index (SPI) and the Palmer drought severity index (PDSI) and streamflow data in 10 regions of China. Sims et al. ( Sims et al. 2002 ) compared the PDSI and the SPI to assess soil moisture variations in North Carolina. In relation to vegetation activity and crop productivity, Potop ( Potop

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Eleanor J. Burke, Simon J. Brown, and Nikolaos Christidis

1985 ; World Meteorological Organization 1975 ; Svoboda et al. 2002 ). These drought indices all have their own advantages and disadvantages ( Keyantash and Dracup 2002 ). The Palmer Drought Severity Index (PDSI; Palmer 1965 ) is a commonly used and widely accepted meteorological drought index (e.g., Cook et al. 1999 ; Dai et al. 2004 ; Lloyd-Hughes and Saunders 2002 ; Ntale and Gan 2003 ; Shabbar and Skinner 2004 ; ). It is obtained from a simplistic model of the

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Daniel J. McEvoy, Justin L. Huntington, John T. Abatzoglou, and Laura M. Edwards

drought in Nevada and eastern California, an arid region with minimal agriculture and population and sparse water availability. One of the first and most highly used drought indices is the Palmer drought severity index (PDSI; Palmer 1965 ), which is based on a simplified soil–water balance. While the PDSI has been well established for adequately explaining many observed wet and dry climate cycles, it has some limitations because of the many parameterizations of the calculation and the lack of ability

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Jinyoung Rhee, Gregory J. Carbone, and James Hussey

approximate spatial distributions of drought. This paper investigates the influence of spatial interpolation and aggregation of data to depict drought at various spatial units. Drought monitoring often uses one or more indices, such as the Palmer drought index (PDI; Palmer 1965 ) or the standardized precipitation index (SPI; McKee et al. 1993 ), to measure drought intensity. These indices can be calculated at individual weather stations or for a specified area; for example, the PDI is commonly

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Nathan Wells, Steve Goddard, and Michael J. Hayes

1. Introduction The Palmer Drought Severity Index (PDSI) ( Palmer 1965 ) was one of the first procedures to demonstrate success at quantifying the severity of droughts across different climates. Palmer's objective was to “develop a general methodology for evaluating (the drought) in terms of an index that permits time and space comparisons of drought severity” ( Palmer 1965 ). Instead of being based purely on precipitation, the PDSI is based upon a primitive water balance model. As detailed in

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Zengchao Hao and Amir AghaKouchak

( Hayes et al. 2011 ). Different drought indices have been developed and applied for drought monitoring and prediction. The Palmer drought severity index (PDSI; Palmer 1965 ) is widely used for drought characterization ( Dai et al. 2004 ; Dai 2011 ). The standardized precipitation index (SPI) proposed by McKee et al. (1993) is commonly used for meteorological drought monitoring and has been adopted as an important monitoring tool to detect the early emergence of drought ( Shukla et al. 2011 ). The

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S. M. Vicente-Serrano, S. Beguería, J. I. López-Moreno, M. Angulo, and A. El Kenawy

of drought indices ( Heim 2002 ; Keyantash and Dracup 2002 ). Among various indices for drought detection, the Palmer drought severity index (PDSI; Palmer 1965 ) is one of the most widely used; the calculation procedure for this index has been described in several studies (e.g., Karl 1983 , 1986 ; Alley 1984 ). This is a climatic water balance index that considers precipitation and evapotranspiration anomalies and soil water-holding capacity. Many of the PDSI deficiencies were resolved by

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Ashok K. Mishra and Vijay P. Singh

variables for agricultural drought forecasting. Rao and Padmanabhan ( Rao and Padmanabhan 1984 ) used the Palmer drought index (PDI) to forecast and simulate PDI series. Mishra and Desai ( Mishra and Desai 2005 ) developed linear stochastic models [Autoregressive Integrated Moving Average (ARIMA) and Seasonal ARIMA (SARIMA)] for forecasting droughts with the use of the standardized precipitation index (SPI) series as a drought quantifying parameter and Han et al. ( Han et al. 2010 ) used an ARIMA model

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William M. Alley

1100JOURNAL OF CLIMATE AND APPLIED METEOROLOGYVOLUME 23The Palmer Drought Severity Index: Limitations and AssumptionsWILLIAM M. ALLEYU.S. Geological Survey. Reston, VA 22092(Manuscript received 19 March 1984, in final form 30 April 1984)ABSTRACTThe structure of the Palmer Drought Severity Index (PDSI), which is perhaps the most widely usedregional index of drought, is examined. The PDSI addresses two of the most elusive properties of droughts:their intensity and their beginning and ending times

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Daniel J. McEvoy, Justin L. Huntington, Michael T. Hobbins, Andrew Wood, Charles Morton, Martha Anderson, and Christopher Hain

relationship between actual evapotranspiration (ET) and atmospheric evaporative demand E 0 . It has been common practice in recent decades to monitor and analyze drought using metrics driven by Prcp and T air only. The two most commonly used drought indices are the Palmer drought severity index (PDSI; Palmer 1965 ), which relies on monthly T air and Prcp, and the Standardized Precipitation Index (SPI; McKee et al. 1993 ), which relies on Prcp only. While the PDSI and SPI have proven useful for

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